A finite-sample deviation bound for stable autoregressive processes
RA González, CR Rojas - Learning for Dynamics and Control, 2020 - proceedings.mlr.press
In this paper, we study non-asymptotic deviation bounds of the least squares estimator in
Gaussian AR ($ n $) processes. By relying on martingale concentration inequalities and a …
Gaussian AR ($ n $) processes. By relying on martingale concentration inequalities and a …
Linear convergence of gradient methods for estimating structured transition matrices in high-dimensional vector autoregressive models
X Lv, W Cui, Y Liu - Advances in Neural Information …, 2021 - proceedings.neurips.cc
In this paper, we present non-asymptotic optimization guarantees of gradient descent
methods for estimating structured transition matrices in high-dimensional vector …
methods for estimating structured transition matrices in high-dimensional vector …
Continuous-time System Identification: Refined Instrumental Variables and Sampling Assumptions
R González - 2022 - research.tue.nl
Continuous-time system identification deals with the problem of building continuous-time
models of dynamical systems from sampled input and output data. There are two main …
models of dynamical systems from sampled input and output data. There are two main …
Consistency and efficiency in continuous-time system identification
RA González - 2020 - diva-portal.org
Continuous-time system identification deals with the problem of building continuoustime
models of dynamical systems from sampled input and output data. In this field, there are two …
models of dynamical systems from sampled input and output data. In this field, there are two …